Learning Excel: Data Analysis

Description

In this course, you will learn :

• Differentiate between the mean, median, and mode.
• Explain the connection between variance and standard deviation.
• Choose a nondirectional hypothesis.
• Explain the distinction between COVARIANCE.P and COVARIANCE.S.
• Explain the relationship.
• Examine Bayes' rule.

Syllabus :

1. Foundational Concepts of Data Analysis

• Calculate mean and median values
• Measure maximums, minimums, and other data characteristics
• Analyze data using variance and standard deviation
• Introducing the central limit theorem
• Analyze a population using data samples
• Identify and minimize sources of error

 

2. Visualize Data

• Group data using histograms
• Identify relationships using XY scatter charts
• Visualize data using logarithmic scales
• Add trendlines to charts
• Forecast future results
• Calculate running averages

 

3. Test a Hypothesis

• Formulate a hypothesis
• Interpret the results of your analysis
• Consider the limits of hypothesis testing

 

4. Utilize Data Distributions

• Use the normal distribution
• Use the exponential distribution
• Use a uniform distribution
• Use the binomial distribution
• Use the Poisson distribution

 

5. Measure Covariance and Correlation

• Visualize what covariance means
• Calculate covariance between two columns of data
• Calculate covariance among multiple pairs of columns
• Visualize what correlation means
• Calculate correlation between two columns of data
• Calculate correlation among multiple pairs of columns

 

6. Perform Bayesian Analysis

• Introduce Bayesian analysis
• Analyze a sample problem: Kahneman’s Cabs
• Create a classification matrix
• Calculate Bayesian probabilities in Excel
• Update your Bayesian analysis

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